Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
388588 | Expert Systems with Applications | 2007 | 12 Pages |
Abstract
One of the significant research problems in multivariate analysis is the selection of a subset of input variables that can predict the desired output with an acceptable level of accuracy. This goal is attained through the elimination of the variables that produce noise or, are strictly correlated with other already selected variables. Feature subset selection (selection of the input variables) is important in correlation analysis and in the field of classification and modeling. This paper presents a hybrid method based on ant colony optimization and artificial neural networks (ANNs) to address feature selection. The proposed hybrid model is demonstrated using data sets from the domain of medical diagnosis, yielding promising results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Rahul Karthik Sivagaminathan, Sreeram Ramakrishnan,